S. References, M. Ali, and . Shah, Human action recognition in videos using kinematic features and multiple instance learning, IEEE TPAMI, vol.32, 2010.

J. Alon, V. Athitsos, Q. Yuan, and S. Sclaroff, A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.9, pp.311685-1699, 2009.
DOI : 10.1109/TPAMI.2008.203

URL : http://cs-people.bu.edu/athitsos/publications/alon_pami_preprint.pdf

M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele, 2D Human Pose Estimation: New Benchmark and State of the Art Analysis, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014.
DOI : 10.1109/CVPR.2014.471

J. Appenrodt, A. Al-hamadi, M. Elmezain, and B. Michaelis, Data Gathering for Gesture Recognition Systems Based on Mono Color-, Stereo Color- and Thermal Cameras, Proceedings of the 1st International Conference on Future Generation Information Technology, FGIT '09, pp.78-86, 2009.
DOI : 10.1007/978-3-642-10509-8_10

V. Athitsos and S. Sclaroff, Estimating 3D hand pose from a cluttered image, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., pp.432-439, 2003.
DOI : 10.1109/CVPR.2003.1211500

URL : http://cs-people.bu.edu/athitsos/publications/athitsos_cvpr2003.pdf

V. Athitsos, C. Neidle, S. Sclaroff, J. Nash, A. Stefan et al., The American Sign Language Lexicon Video Dataset, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008.
DOI : 10.1109/CVPRW.2008.4563181

URL : http://cs-people.bu.edu/athitsos/publications/athitsos_cvpr4hb2008.pdf

A. Avci, S. Bosch, M. Marin-perianu, R. Marin-perianu, and P. J. Havinga, Activity recognition using inertial sensing for healthcare, wellbeing and sports applications: A survey, ARCS Workshops, pp.167-176, 2010.

L. Baraldi, F. Paci, G. Serra, L. Benini, and R. Cucchiara, Gesture Recognition in Ego-centric Videos Using Dense Trajectories and Hand Segmentation, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014.
DOI : 10.1109/CVPRW.2014.107

X. Baró, J. Gonzàlez, J. Fabian, M. A. Bautista, M. Oliu et al., ChaLearn Looking at People 2015 challenges: Action spotting and cultural event recognition, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2015.
DOI : 10.1109/CVPRW.2015.7301329

B. Bauer, H. Hienz, and K. Kraiss, Video-based continuous sign language recognition using statistical methods, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.2463-2466, 2000.
DOI : 10.1109/ICPR.2000.906112

A. Y. Benbasat and J. A. Paradiso, Compact, configurable inertial gesture recognition, CHI '01 extended abstracts on Human factors in computing systems , CHI '01, pp.183-184, 2001.
DOI : 10.1145/634067.634178

URL : http://www.media.mit.edu/resenv/pubs/papers/2001-04-chi-imu.pdf

S. Berlemont, G. Lefebvre, S. Duffner, and C. Garcia, Siamese neural network based similarity metric for inertial gesture classification and rejection. Automatic Face and Gesture Recognition, 2015.
DOI : 10.1109/fg.2015.7163112

URL : https://hal.archives-ouvertes.fr/hal-01179993

V. Bloom, D. Makris, and V. Argyriou, G3D: A gaming action dataset and real time action recognition evaluation framework, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.7-12, 2012.
DOI : 10.1109/CVPRW.2012.6239175

A. F. Bobick and J. W. Davis, The recognition of human movement using temporal templates, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.3, pp.257-267, 2001.
DOI : 10.1109/34.910878

L. Bourdev and J. Malik, Poselets: Body part detectors trained using 3D human pose annotations, 2009 IEEE 12th International Conference on Computer Vision, pp.1365-1372, 2009.
DOI : 10.1109/ICCV.2009.5459303

M. Brand, N. Oliver, and A. P. Pentland, Coupled hidden Markov models for complex action recognition, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.994-999, 1997.
DOI : 10.1109/CVPR.1997.609450

URL : ftp://whitechapel.media.mit.edu/pub/tech-reports/TR-407.ps.Z

M. Caon, Y. Yong, J. Tscherrig, E. Mugellini, and O. A. Khaled, Context-aware 3D gesture interaction based on multiple Kinects, The First International Conference on Ambient Computing, Applications, Services and Technologies, p.712, 2011.

G. Castellano, S. D. Villalba, and A. Camurri, Recognising Human Emotions from Body Movement and Gesture Dynamics, Affective computing and intelligent interaction, pp.71-82, 2007.
DOI : 10.1007/978-3-540-74889-2_7

A. Chaudhary, J. L. Raheja, K. Das, and S. Raheja, A Survey on Hand Gesture Recognition in Context of Soft Computing, pp.46-55, 2011.
DOI : 10.1145/1529282.1529652

F. S. Chen, C. M. Fu, and C. L. Huang, Hand gesture recognition using a real-time tracking method and hidden Markov models, Image and Vision Computing, vol.21, issue.8, pp.745-758, 2003.
DOI : 10.1016/S0262-8856(03)00070-2

M. Chen, G. Alregib, and B. Juang, 6DMG, Proceedings of the 3rd Multimedia Systems Conference on, MMSys '12, pp.83-88, 2012.
DOI : 10.1145/2155555.2155569

C. Conly, P. Doliotis, P. Jangyodsuk, R. Alonzo, and V. Athitsos, Toward a 3D body part detection video dataset and hand tracking benchmark, Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA '13, 2013.
DOI : 10.1145/2504335.2504337

URL : http://vlm1.uta.edu/%7Edoliotis/publications/doliotis_petra2013.pdf

C. Conly, Z. Zhang, and V. Athitsos, An integrated RGB-D system for looking up the meaning of signs, Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA '15, 2015.
DOI : 10.1007/11492429_63

H. Cooper and R. Bowden, Learning signs from subtitles: A weakly supervised approach to sign language recognition, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.2568-2574, 2009.
DOI : 10.1109/CVPR.2009.5206647

URL : http://www.ee.surrey.ac.uk/Personal/R.Bowden/publications/cvpr2009/1512.pdf

H. Cooper, E. Ong, N. Pugeault, and R. Bowden, Sign Language Recognition Using Sub-units, Journal of Machine Learning Research (JMLR), vol.3, issue.3, pp.2205-2231, 2012.
DOI : 10.1145/2070481.2070532

URL : http://epubs.surrey.ac.uk/808972/1/Cooper_JMLR_2012.pdf

A. Corradini, Dynamic time warping for off-line recognition of a small gesture vocabulary, Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp.82-89, 2001.
DOI : 10.1109/RATFG.2001.938914

Y. Cui and J. Weng, Appearance-Based Hand Sign Recognition from Intensity Image Sequences, Computer Vision and Image Understanding, vol.78, issue.2, pp.157-176, 2000.
DOI : 10.1006/cviu.2000.0837

URL : http://www.cse.msu.edu/~weng/research/SHOSLIF-M-rec.ps

R. Cutler and M. Turk, View-based interpretation of real-time optical flow for gesture recognition, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, pp.416-421, 1998.
DOI : 10.1109/AFGR.1998.670984

A. Czabke, J. Neuhauser, and T. C. Lueth, Recognition of interactions with objects based on radio modules, Proceedings of the 4th International ICST Conference on Pervasive Computing Technologies for Healthcare, 2010.
DOI : 10.4108/ICST.PERVASIVEHEALTH2010.8860

T. J. Darrell, I. A. Essa, and A. P. Pentland, Task-specific gesture analysis in real-time using interpolated views, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.12, pp.1236-1242, 1996.
DOI : 10.1109/34.546259

URL : http://www-white.media.mit.edu/vismod/publications/techdir/TR-364.ps.Z

M. De-la-gorce, D. J. Fleet, and N. Paragios, Model-Based 3D Hand Pose Estimation from Monocular Video, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.9, pp.1793-1805, 2011.
DOI : 10.1109/TPAMI.2011.33

URL : https://hal.archives-ouvertes.fr/hal-00856313

D. Demirdjian and C. Varri, Recognizing events with temporal random forests, Proceedings of the 2009 international conference on Multimodal interfaces, ICMI-MLMI '09, pp.293-296, 2009.
DOI : 10.1145/1647314.1647377

K. Derpanis, . Sizintsev, R. Kj-cannons, and . Wildes, Action Spotting and Recognition Based on a Spatiotemporal Orientation Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.3, pp.527-540, 2013.
DOI : 10.1109/TPAMI.2012.141

URL : http://www.cse.yorku.ca/vision/publications/pami2013DerpanisSizintsevCannonsWildes.pdf

P. Dreuw, T. Deselaers, D. Keysers, and H. Ney, Modeling image variability in appearance-based gesture recognition, ECCV Workshop on Statistical Methods in Multi-Image and Video Processing, pp.7-18, 2006.

S. Duffner, S. Berlemont, G. Lefebvre, and C. Garcia, 3D gesture classification with convolutional neural networks, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p.2014
DOI : 10.1109/ICASSP.2014.6854641

URL : https://hal.archives-ouvertes.fr/hal-01180542

U. M. Erdem and S. Sclaroff, Automatic detection of relevant head gestures in American Sign Language communication, Object recognition supported by user interaction for service robots, pp.460-463, 2002.
DOI : 10.1109/ICPR.2002.1044759

S. Escalera, J. Gonzàlez, X. Baró, M. Reyes, I. Guyon et al., ChaLearn multi-modal gesture recognition 2013, Proceedings of the 15th ACM on International conference on multimodal interaction, ICMI '13, pp.365-368, 2013.
DOI : 10.1145/2522848.2532597

S. Escalera, J. Gonzàlez, X. Baró, M. Reyes, O. Lopés et al., Multi-modal gesture recognition challenge 2013, Proceedings of the 15th ACM on International conference on multimodal interaction, ICMI '13, 2013.
DOI : 10.1145/2522848.2532595

URL : https://hal.archives-ouvertes.fr/hal-01381153

S. R. Fanello, I. Gori, G. Metta, and F. Odone, Keep It Simple and Sparse: Real-Time Action Recognition, Journal of Machine Learning Research, vol.5303, issue.1, pp.2617-2640, 2013.
DOI : 10.1007/s11263-010-0404-0

A. Farhadi, D. A. Forsyth, and R. White, Transfer Learning in Sign language, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383346

URL : http://luthuli.cs.uiuc.edu/~daf/courses/Signals AI/Papers/HMMs/farhadi2007cvpr.pdf

A. Fathi, X. Ren, and J. M. Rehg, Learning to recognize objects in egocentric activities, CVPR 2011, pp.3281-3288
DOI : 10.1109/CVPR.2011.5995444

S. S. Fels, Glove-TalkII, Proceedings of the SIGCHI conference on Human factors in computing systems, CHI '95, 1994.
DOI : 10.1145/223904.223966

V. Ferrari, M. Marin-jimenez, and A. Zisserman, Progressive search space reduction for human pose estimation, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008.
DOI : 10.1109/CVPR.2008.4587468

URL : http://eprints.pascal-network.org/archive/00004745/01/cvpr.pdf

S. Fothergill, H. Mentis, P. Kohli, and S. Nowozin, Instructing people for training gestural interactive systems, Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems, CHI '12, pp.1737-1746, 2012.
DOI : 10.1145/2207676.2208303

URL : http://research.microsoft.com/en-us/um/people/pkohli/papers/fmkn_chi2012.pdf

W. T. Freeman and M. Roth, Computer vision for computer games, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition, pp.100-105, 1996.
DOI : 10.1109/AFGR.1996.557250

W. T. Freeman and C. D. Weissman, Television control by hand gestures, 1994.

N. Gillian and J. A. Paradiso, The Gesture Recognition Toolkit, Journal of Machine Learning Research, vol.11, issue.6, p.14, 2014.
DOI : 10.1145/1866029.1866038

URL : http://dspace.mit.edu/bitstream/1721.1/103640/1/Paradiso_The%20gesture.pdf

A. Gorban, H. Idrees, Y. Jiang, A. Zamir, I. Laptev et al., THU- MOS challenge: Action recognition with a large number of classes, 2015.

L. Gorelick, M. Blank, E. Shechtman, M. Irani, and R. Basri, Actions as Space-Time Shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.12, pp.2247-2253, 2007.
DOI : 10.1109/TPAMI.2007.70711

URL : http://www.wisdom.weizmann.ac.il/~yelenag/spaceTimeActionsTPAMI2007.pdf

N. Goussies, S. Ubalde, and M. Mejail, Transfer Learning Decision Forests for Gesture Recognition, Journal of Machine Learning Research, vol.14, issue.2, p.2014
DOI : 10.1109/CVPR.2010.5539857

M. Gowing, A. Ahmadi, F. Destelle, D. S. Monaghan, N. E. O-'connor et al., Kinect vs. Low-cost Inertial Sensing for Gesture Recognition, Lecture Notes in Computer Science, vol.8325, pp.484-495, 2014.
DOI : 10.1007/978-3-319-04114-8_41

I. Guyon, V. Athitsos, P. Jangyodsuk, H. J. Escalante, and B. Hamner, Results and Analysis of the ChaLearn Gesture Challenge 2012, Lecture Notes in Computer Science, vol.7854, pp.186-204978
DOI : 10.1007/978-3-642-40303-3_19

I. Guyon, V. Athitsos, P. Jangyodsuk, and H. J. Escalante, The ChaLearn gesture dataset, Machine Vision and Applications, pp.1929-1951, 2011.
DOI : 10.1007/s00138-014-0596-3

URL : https://hal.archives-ouvertes.fr/hal-01381163

A. Hernandez-vela, N. Zlateva, A. Marinov, M. Reyes, P. Radeva et al., Graph cuts optimization for multi-limb human segmentation in depth maps, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247742

URL : http://www.cvc.uab.cat/%7Eahernandez/files/cvpr2012.pdf

A. Hernandez-vela, M. A. Bautista, X. Perez-sala, V. Ponce, S. Escalera et al., Probability-based dynamic time warping and bag-of-visual-anddepth-words for human gesture recognition in RGB-D, Pattern Recognition Letters, 2013.

A. Hernandez-vela, M. Reyes, V. Ponce, and S. Escalera, GrabCut-Based Human Segmentation in Video Sequences, Sensors, vol.31, issue.12, pp.15376-15393, 2013.
DOI : 10.1109/TPAMI.2008.203

G. Hewes, Primate Communication and the Gestural Origin of Language, Current Anthropology, vol.33, issue.S1, pp.5-24, 1973.
DOI : 10.1086/204019

N. A. Ibraheem and R. Z. Khan, Survey on various gesture recognition technologies and techniques, International Journal of Computer Applications, vol.50, issue.7, pp.38-44, 2012.

C. Ionescu, D. Papava, V. Olaru, C. Sminchisescu, and . Human3, Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.7, pp.1325-1339, 2014.
DOI : 10.1109/TPAMI.2013.248

M. Isard and A. Blake, CONDENSATION -conditional density propagation for visual tracking, International Journal of Computer Vision, vol.29, issue.1, pp.5-28, 1998.
DOI : 10.1023/A:1008078328650

H. Jegou, F. Perronnin, M. Douze, J. Sanchez, P. Perez et al., Aggregating Local Image Descriptors into Compact Codes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.9, pp.1704-1716, 2012.
DOI : 10.1109/TPAMI.2011.235

URL : https://hal.archives-ouvertes.fr/inria-00633013

F. Jiang, S. Zhang, S. Wu, Y. Gao, and D. Zhao, Multi-layered Gesture Recognition with Kinect, Journal of Machine Learning Research, vol.23, issue.2, p.2015
DOI : 10.1145/1027933.1027967

S. Johnson and M. Everingham, Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation, Procedings of the British Machine Vision Conference 2010
DOI : 10.5244/C.24.12

URL : http://www.comp.leeds.ac.uk/mat4saj/publications/johnson10bmvc.pdf

A. Joshi, S. Sclaroff, M. Betke, and C. Monnier, A random forest approach to segmenting and classifying gestures. Automatic Face and Gesture Recognition, 2015.
DOI : 10.1109/fg.2015.7163126

URL : https://open.bu.edu/bitstream/2144/15405/1/Joshi_bu_0017N_10851.pdf

T. Kadir, R. Bowden, E. Ong, and A. Zisserman, Minimal Training, Large Lexicon, Unconstrained Sign Language Recognition, Procedings of the British Machine Vision Conference 2004, pp.939-948, 2004.
DOI : 10.5244/C.18.96

URL : http://www.bmva.org/bmvc/2004/papers/paper_265.pdf

K. Kahol, P. Tripathi, and S. Panchanathan, Automated gesture segmentation from dance sequences, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings., pp.883-888, 2004.
DOI : 10.1109/AFGR.2004.1301645

URL : http://www.public.asu.edu/~kkahol/publications/kanavfandgesture2004.pdf

H. Kang, C. W. Lee, and K. Jung, Recognition-based gesture spotting in video games, Pattern Recognition Letters, vol.25, issue.15, pp.1701-1714, 2004.
DOI : 10.1016/j.patrec.2004.06.016

A. Kapur, A. Kapur, N. Virji-babul, G. Tzanetakis, and P. F. Driessen, Gesture-Based Affective Computing on Motion Capture Data, Affective Computing and Intelligent Interaction, pp.1-7, 2005.
DOI : 10.1007/11573548_1

URL : http://webhome.cs.uvic.ca/~gtzan/work/pubs/acii05gtzan.pdf

S. Kausar and M. Y. Javed, A Survey on Sign Language Recognition, 2011 Frontiers of Information Technology, pp.95-98, 2011.
DOI : 10.1109/FIT.2011.25

Y. Ke, R. Sukthankar, and M. Hebert, Efficient visual event detection using volumetric features, IEEE International Conference on Computer Vision (ICCV), pp.166-173, 2005.

D. Kelly, J. Mcdonald, and C. Markham, A person independent system for recognition of hand postures used in sign language, Pattern Recognition Letters, vol.31, issue.11, pp.311359-1368, 2010.
DOI : 10.1016/j.patrec.2010.02.004

C. Keskin, F. K?raç, Y. E. Kara, and L. Akarun, Hand Pose Estimation and Hand Shape Classification Using Multi-layered Randomized Decision Forests, European Conference on Computer Vision (ECCV), pp.852-863, 2012.
DOI : 10.1007/978-3-642-33783-3_61

R. Z. Khan and N. A. Ibraheem, Survey on Gesture Recognition for Hand Image Postures, Computer and Information Science, vol.5, issue.3
DOI : 10.5539/cis.v5n3p110

URL : http://www.ccsenet.org/journal/index.php/cis/article/download/16598/11060/

T. Kim, S. Wong, and R. Cipolla, Tensor Canonical Correlation Analysis for Action Classification, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383137

H. Kjellström, J. Romero, D. Martínez, and D. Kragi´ckragi´c, Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects, European Conference on Computer Vision, pp.336-349, 2008.
DOI : 10.1109/CVPR.2007.383299

D. K. Kohlsdorf and T. E. Starner, MAGIC Summoning: Towards Automatic Suggesting and Testing of Gestures with Low Probability of False Positives During Use, Journal of Machine Learning Research, vol.31, issue.7, pp.209-242, 2013.
DOI : 10.1109/TPAMI.2008.172

M. Kolsch and M. Turk, Fast 2D Hand Tracking with Flocks of Features and Multi-Cue Integration, 2004 Conference on Computer Vision and Pattern Recognition Workshop, pp.158-165, 2004.
DOI : 10.1109/CVPR.2004.345

J. Konecny and M. Hagara, One-shot-learning gesture recognition using hog-hof features, Journal of Machine Learning Research, vol.15, pp.2513-2532, 2014.

Y. Kong, B. Satarboroujeni, and Y. Fu, Hierarchical 3D kernel descriptors for action recognition using depth sequences. Automatic Face and Gesture Recognition, 2015.

J. B. Kruskal and M. Liberman, The symmetric time warping algorithm: From continuous to discrete, Time Warps, 1983.

A. Kurakin, Z. Zhang, and Z. Liu, A real time system for dynamic hand gesture recognition with a depth sensor, European Signal Processing Conference, EUSIPCO, pp.1975-1979, 2012.

J. D. Lafferty, A. Mccallum, and F. C. Pereira, Conditional random fields: Probabilistic models for segmenting and labeling sequence data, International Conference on Machine Learning (ICML), pp.282-289, 2001.

H. Lane, R. J. Hoffmeister, and B. Bahan, A Journey into the Deaf-World, 1996.

I. Laptev, On Space-Time Interest Points, International Journal of Computer Vision, vol.17, issue.8, pp.107-123, 2005.
DOI : 10.1007/BFb0017862

URL : http://kth.diva-portal.org/smash/get/diva2:442088/FULLTEXT01

I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, Learning realistic human actions from movies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587756

URL : https://hal.archives-ouvertes.fr/inria-00548659

E. Larson, G. Cohn, S. Gupta, X. Ren, B. Harrison et al., HeatWave, Proceedings of the 2011 annual conference on Human factors in computing systems, CHI '11, pp.2565-2574, 2011.
DOI : 10.1145/1978942.1979317

J. J. Laviola-jr, A survey of hand posture and gesture recognition techniques and technology, 1999.

H. K. Lee and J. H. Kim, An HMM-based threshold model approach for gesture recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.10, pp.961-973, 1999.

S. Lee, Automatic gesture recognition for intelligent human-robot interaction, IEEE International Conference on Automatic Face and Gesture Recognition, pp.645-650, 2006.

C. Li and K. M. Kitani, Pixel-Level Hand Detection in Ego-centric Videos, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.458

URL : http://www.cs.cmu.edu/~kkitani/Publications_files/LK-CVPR2013.pdf

W. Li, Z. Zhang, and Z. Liu, Action recognition based on a bag of 3D points, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Workshops, pp.9-14, 2010.
DOI : 10.1109/CVPRW.2010.5543273

H. Liang, J. Yuan, D. Thalmann, and Z. Zhang, Model-based hand pose estimation via spatialtemporal hand parsing and 3D fingertip localization, The Visual Computer, vol.29, pp.6-8837, 2013.
DOI : 10.1007/s00371-013-0822-4

H. Liang, J. Yuan, and D. Thalmann, Parsing the Hand in Depth Images, IEEE Transactions on Multimedia, vol.16, issue.5, pp.1241-1253, 2014.
DOI : 10.1109/TMM.2014.2306177

A. Licsár and T. Szirányi, Hand Gesture Recognition in Camera-Projector System*, Computer Vision in Human-Computer Interaction, pp.83-93, 2004.
DOI : 10.1007/978-3-540-24837-8_9

Z. Lin, Z. Jiang, and L. S. Davis, Recognizing actions by shape-motion prototype trees, IEEE International Conference on Computer Vision, ICCV, pp.444-451, 2009.

K. Liu, C. Chen, R. Jafari, and N. Kehtarnavaz, Fusion of inertial and depth sensor data for robust hand gesture recognition, IEEE Sensors Journal, vol.14, issue.6, pp.1898-1903, 2014.

L. Liu and L. Shao, Learning discriminative representations from RGB-D video data, International Joint Conference on Artificial Intelligence (IJCAI), pp.1493-1500, 2013.

O. Lopes, M. Reyes, S. Escalera, and J. Gonzàlez, Spherical Blurred Shape Model for 3-D Object and Pose Recognition: Quantitative Analysis and HCI Applications in Smart Environments, IEEE Transactions on Cybernetics, vol.44, issue.12, pp.442379-2390, 2014.
DOI : 10.1109/TCYB.2014.2307121

Y. M. Lui, Human Gesture Recognition on Product Manifolds, Journal of Machine Learning Research (JMLR), vol.104, issue.12, pp.3297-3321, 2012.
DOI : 10.1016/j.cviu.2006.07.013

J. Luo, W. Wang, and H. Qi, Spatio-temporal feature extraction and representation for RGB-D human action recognition, Pattern Recognition Letters, vol.50, 2014.
DOI : 10.1016/j.patrec.2014.03.024

J. Ma, W. Gao, J. Wu, and C. Wang, A continuous Chinese Sign Language recognition system, Automatic Face and Gesture Recognition, pp.428-433, 2000.

S. Ma, J. Zhang, N. Ikizler-cinbis, and S. Sclaroff, Action Recognition and Localization by Hierarchical Space-Time Segments, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.341

URL : http://cs-people.bu.edu/shugaoma/STSegments/iccv2013_preprint_shugao.pdf

M. R. Malgireddy, I. Nwogu, and V. Govindaraju, Language-Motivated Approaches to Action Recognition, Journal of Machine Learning Research, vol.22, issue.8, pp.2189-2212, 2013.
DOI : 10.1109/CVPR.2009.5206671

S. Malik and J. Laszlo, Visual touchpad, Proceedings of the 6th international conference on Multimodal interfaces , ICMI '04, pp.289-296, 2004.
DOI : 10.1145/1027933.1027980

J. Martin, V. Devin, and J. L. Crowley, Active hand tracking, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, pp.573-578, 1998.
DOI : 10.1109/AFGR.1998.671009

A. Martinez and S. Du, A Model of the Perception of Facial Expressions of Emotion by Humans: Research Overview and Perspectives, Journal of Machine Learning Research, vol.98, issue.2, pp.1589-1608, 2012.
DOI : 10.1037/a0017990

D. Mcneil, How language began, gesture and speech in human evolution. Cambridge editorial, 2012.

S. Mitra and T. Acharya, Gesture Recognition: A Survey, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol.37, issue.3, pp.311-324, 2007.
DOI : 10.1109/TSMCC.2007.893280

Z. Mo and U. Neumann, Real-time hand pose recognition using low-resolution depth images, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1499-1505, 2006.

B. Moghaddam and A. Pentland, Probabilistic visual learning for object detection, Proceedings of IEEE International Conference on Computer Vision, 1995.
DOI : 10.1109/ICCV.1995.466858

URL : http://www-white.media.mit.edu/vismod/publications/techdir/TR-326.ps.Z

P. Molchanov, S. Gupta, K. Kim, and K. Pulli, Multi-sensor system for drivers hand-gesture recognition . Automatic Face and Gesture Recognition, 2015.
DOI : 10.1109/fg.2015.7163132

J. Nagi, F. Ducatelle, G. A. Di-caro, D. C. Ciresan, U. Meier et al., Max-pooling convolutional neural networks for vision-based hand gesture recognition, 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), pp.342-347, 2011.
DOI : 10.1109/ICSIPA.2011.6144164

URL : http://www.idsia.ch/~juergen/icsipa2011.pdf

S. Nayak, S. Sarkar, and B. Loeding, Unsupervised Modeling of Signs Embedded in Continuous Sentences, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), Workshops, 2005.
DOI : 10.1109/CVPR.2005.547

S. Nayak, K. Duncan, S. Sarkar, and B. Loeding, Finding Recurrent Patterns from Continuous Sign Language Sentences for Automated Extraction of Signs, Journal of Machine Learning Research (JMLR), vol.32, issue.3, pp.2589-2615, 2012.
DOI : 10.1109/TPAMI.2009.26

C. Neidle, A. Thangali, and S. Sclaroff, Challenges in development of the American Sign Language lexicon video dataset (ASLLVD) corpus, Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon, 2012.

N. Neverova, C. Wolf, G. W. Taylor, and F. Nebout, Multi-scale Deep Learning for Gesture Detection and Localization, ChaLearn Looking at People, European Conference on Computer Vision, 2014.
DOI : 10.1007/978-3-319-16178-5_33

URL : https://hal.archives-ouvertes.fr/hal-01419792

L. Nguyen-dinh, A. Calatroni, and G. Troster, Robust Online Gesture Recognition with Crowdsourced Annotations, Journal of Machine Learning Research, vol.34, issue.7, p.15, 2014.
DOI : 10.1007/978-3-540-77690-1_2

E. Ohn-bar and M. M. Trivedi, Hand Gesture Recognition in Real Time for Automotive Interfaces: A Multimodal Vision-Based Approach and Evaluations, IEEE Transactions on Intelligent Transportation Systems, vol.15, issue.6, 2014.
DOI : 10.1109/TITS.2014.2337331

I. Oikonomidis, N. Kyriazis, and A. A. Argyros, Markerless and Efficient 26-DOF Hand Pose Recovery, Asian Conference on Computer Vision (ACCV), 2010.
DOI : 10.1080/2151237X.2006.10129229

I. Oikonomidis, N. Kyriazis, and A. A. Argyros, Full DOF tracking of a hand interacting with an object by modeling occlusions and physical constraints, 2011 International Conference on Computer Vision, pp.2088-2095, 2011.
DOI : 10.1109/ICCV.2011.6126483

K. Oka, Y. Sato, and H. Koike, Real-time fingertip tracking and gesture recognition, IEEE Computer Graphics and Applications, vol.22, issue.6, pp.64-71, 2002.
DOI : 10.1109/MCG.2002.1046630

R. Oka, Spotting Method for Classification of Real World Data, The Computer Journal, vol.41, issue.8, pp.559-565, 1998.
DOI : 10.1093/comjnl/41.8.559

E. J. Ong and R. Bowden, A boosted classifier tree for hand shape detection, Face and Gesture Recognition, pp.889-894, 2004.

O. Oreifej and Z. Liu, HON4D: Histogram of Oriented 4D Normals for Activity Recognition from Depth Sequences, 2013 IEEE Conference on Computer Vision and Pattern Recognition, pp.716-723, 2013.
DOI : 10.1109/CVPR.2013.98

A. Pardo, A. Clapes, S. Escalera, and O. Pujol, Actions in Context: System for People with Dementia, 2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems (ECCS'13), 2013.
DOI : 10.1007/978-3-319-04178-0_1

A. Patron-perez, M. Marszalek, A. Zisserman, and I. D. Reid, High five: Recognising human interactions in TV shows, British Machine Vision Conference BMVC, 2010.

X. Peng, L. Wang, Z. Cai, and Y. Qiao, Action and Gesture Temporal Spotting with Super Vector Representation, Lourdes Agapito, Michael M. Bronstein, and Carsten Rother Computer Vision -ECCV 2014 Workshops, pp.518-527978, 2015.
DOI : 10.1007/978-3-319-16178-5_36

A. Pieropan, G. Salvi, K. Pauwels, and H. Kjellstrm, Audio-visual classification and detection of human manipulation actions, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014.
DOI : 10.1109/IROS.2014.6942983

V. Pitsikalis, A. Katsamanis, S. Theodorakis, and P. Maragos, Multimodal Gesture Recognition via Multiple Hypotheses Rescoring, Journal of Machine Learning Research, vol.24, issue.8, p.2014
DOI : 10.1109/TPAMI.2002.1023803

N. Pugeault and R. Bowden, Spelling it out: Real-time ASL fingerspelling recognition, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp.1114-1119, 2011.
DOI : 10.1109/ICCVW.2011.6130290

URL : http://epubs.surrey.ac.uk/531435/1/PugeaultBowden2011b.pdf

A. Quattoni, S. B. Wang, L. Morency, M. Collins, and T. Darrell, Hidden Conditional Random Fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.10, pp.291848-1852, 2007.
DOI : 10.1109/TPAMI.2007.1124

D. Ramanan, Learning to parse images of articulated bodies, NIPS, pp.1129-1136, 2006.

I. Rauschert, P. Agrawal, R. Sharma, S. Fuhrmann, I. Brewer et al., Designing a human-centered, multimodal GIS interface to support emergency management, Proceedings of the tenth ACM international symposium on Advances in geographic information systems , GIS '02, pp.119-124, 2002.
DOI : 10.1145/585147.585172

URL : http://vision.cse.psu.edu/rauscher/DAVE_G/p90-rauschert.pdf

J. M. Rehg and T. Kanade, Model-based tracking of self-occluding articulated objects, Proceedings of IEEE International Conference on Computer Vision, pp.612-617, 1995.
DOI : 10.1109/ICCV.1995.466882

Z. Ren, J. Meng, J. Yuan, and Z. Zhang, Robust hand gesture recognition with kinect sensor, Proceedings of the 19th ACM international conference on Multimedia, MM '11, pp.759-760, 2011.
DOI : 10.1145/2072298.2072443

Z. Ren, J. Yuan, and Z. Zhang, Robust hand gesture recognition based on finger-earth mover's distance with a commodity depth camera, Proceedings of the 19th ACM international conference on Multimedia, MM '11, pp.1093-1096, 2011.
DOI : 10.1145/2072298.2071946

Z. Ren, J. Yuan, J. Meng, and Z. Zhang, Robust Part-Based Hand Gesture Recognition Using Kinect Sensor, IEEE Transactions on Multimedia, vol.15, issue.5, pp.1110-1120, 2013.
DOI : 10.1109/TMM.2013.2246148

URL : http://www3.ntu.edu.sg/home/JSYUAN/index_files/papers/Ren_Yuan_Meng_Zhang_TMM13.pdf

A. Roussos, S. Theodorakis, V. Pitsikalis, and P. Maragos, Dynamic affine-invariant shapeappearance handshape features and classification in sign language videos, Journal of Machine Learning Research, vol.14, issue.6, pp.1627-1663, 2013.
DOI : 10.1007/978-3-319-57021-1_8

S. Ruffieux, D. Lalanne, and E. Mugellini, ChAirGest, Proceedings of the 15th ACM on International conference on multimodal interaction, ICMI '13, pp.483-488, 2013.
DOI : 10.1145/2522848.2532590

A. Sadeghipour, L. Morency, and S. Kopp, Gesture-based Object Recognition using Histograms of Guiding Strokes, Procedings of the British Machine Vision Conference 2012, pp.44-45, 2012.
DOI : 10.5244/C.26.44

D. Sánchez, M. A. Bautista, and S. Escalera, HuPBA 8k+: Dataset and ECOC-graphcut based segmentation of human limbs, Neurocomputing, 2014.

B. Sapp and B. Taskar, MODEC: Multimodal Decomposable Models for Human Pose Estimation, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.471

URL : http://homes.cs.washington.edu/~taskar/pubs/modec_cvpr13.pdf

Y. Sato and T. Kobayashi, Extension of hidden Markov models to deal with multiple candidates of observations and its application to mobile-robot-oriented gesture recognition, Object recognition supported by user interaction for service robots, pp.515-519, 2002.
DOI : 10.1109/ICPR.2002.1048351

J. Schein, At home among strangers, 1989.

C. Schuldt, I. Laptev, and B. Caputo, Recognizing human actions: a local SVM approach, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004., pp.32-36, 2004.
DOI : 10.1109/ICPR.2004.1334462

URL : http://www.nada.kth.se/%7Ecaputo/publik/icpr04actions.pdf

N. Shapovalova, W. Gong, M. Pedersoli, F. X. Roca, and J. Gonzalez, On Importance of Interactions and Context in Human Action Recognition, Pattern Recognition and Image Analysis, pp.58-66, 2011.
DOI : 10.1145/1282280.1282340

J. Shotton, A. W. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio et al., Real-time human pose recognition in parts from single depth images, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1297-1304, 2011.
DOI : 10.1007/978-3-642-28661-2_5

L. Sigal, A. O. Balan, and M. J. Black, HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human??Motion, International Journal of Computer Vision, vol.74, issue.3, pp.4-27, 2010.
DOI : 10.1109/TPAMI.1980.6447699

C. Sminchisescu, A. Kanaujia, and D. Metaxas, Conditional models for contextual human motion recognition, Computer Vision and Image Understanding, vol.104, issue.2-3, pp.210-220, 2006.
DOI : 10.1016/j.cviu.2006.07.014

URL : http://paul.rutgers.edu/~kanaujia/MyPapers/ICCV2005.pdf

Y. Song, D. Demirdjian, and R. Davis, Multi-signal gesture recognition using temporal smoothing hidden conditional random fields, Face and Gesture 2011, pp.388-393, 2011.
DOI : 10.1109/FG.2011.5771431

URL : http://dspace.mit.edu/bitstream/handle/1721.1/79361/fg2011-Multi-Signal.pdf%3Bjsessionid%3DA86A9BABD3E7E39E41B1F51B518D5EAB?sequence%3D1

Y. Song, D. Demirdjian, and R. Davis, Tracking body and hands for gesture recognition: NATOPS aircraft handling signals database, Face and Gesture 2011, pp.500-506, 2011.
DOI : 10.1109/FG.2011.5771448

URL : http://rationale.csail.mit.edu/publications/SongDD2011a.pdf

T. Starner and A. Pentland, Real-time American sign language recognition using desk and wearable computer based video, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.12, pp.1371-1375, 1998.
DOI : 10.1109/34.735811

URL : http://luthuli.cs.uiuc.edu/~daf/courses/Signals AI/Papers/HMMs/00735811.pdf

N. Stefanov, A. Galata, and R. Hubbold, Real-time Hand Tracking With Variable-Length Markov Models of Behaviour, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), Workshops, 2005.
DOI : 10.1109/CVPR.2005.518

B. Stenger, A. Thayananthan, P. H. Torr, and R. Cipolla, Filtering using a tree-based estimator, Proceedings Ninth IEEE International Conference on Computer Vision, pp.1063-1070, 2003.
DOI : 10.1109/ICCV.2003.1238467

URL : http://lear.inrialpes.fr/people/triggs/events/iccv03/cdrom/iccv03/1063_stenger.pdf

E. Sudderth, M. Mandel, W. Freeman, and A. Willsky, Distributed occlusion reasoning for tracking with nonparametric belief propagation, Neural Information Processing Systems (NIPS), 2004.

D. Tran and D. Forsyth, Improved Human Parsing with a Full Relational Model, ECCV, pp.227-240, 2010.
DOI : 10.1007/978-3-642-15561-1_17

URL : http://vision.cs.uiuc.edu/~ddtran2/pubs/eccv10-final.pdf

J. Triesch, C. Von, and . Malsburg, A system for person-independent hand posture recognition against complex backgrounds, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.12, pp.1449-1453, 2001.
DOI : 10.1109/34.977568

URL : http://publikationen.ub.uni-frankfurt.de/files/3376/TriMal-PAMI2001.pdf

J. Triesch, C. Von, and . Malsburg, Classification of hand postures against complex backgrounds using elastic graph matching, Image and Vision Computing, vol.20, issue.13-14, pp.13-14937, 2002.
DOI : 10.1016/S0262-8856(02)00100-2

M. Van-den-bergh, E. Koller-meier, and L. Van-gool, Real-Time Body Pose Recognition Using 2D or 3D Haarlets, International Journal of Computer Vision, vol.24, issue.1, pp.72-84, 2009.
DOI : 10.1007/s11263-009-0218-0

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, pp.511-518, 2001.
DOI : 10.1109/CVPR.2001.990517

C. Vogler and D. Metaxas, Parallel hidden Markov models for American sign language recognition, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.116-122, 1999.
DOI : 10.1109/ICCV.1999.791206

URL : http://gri.gallaudet.edu/~cvogler/research/data/cvdm-iccv99.pdf

J. Wan, Q. Ruan, W. Li, and S. Deng, One-Shot Learning Gesture Recognition from RGB-D Data Using Bag of Features, Journal of Machine Learning Research, vol.85, issue.3, pp.2549-2582, 2013.
DOI : 10.1006/cviu.2002.0967

H. Wang and C. Schmid, Action Recognition with Improved Trajectories, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.441

URL : https://hal.archives-ouvertes.fr/hal-00873267

H. Wang, A. Stefan, S. Moradi, V. Athitsos, C. Neidle et al., A System for Large Vocabulary Sign Search, Workshop on Sign, Gesture and Activity (SGA), 2010.
DOI : 10.1007/978-3-642-35749-7_27

URL : http://vlm1.uta.edu/%7Eathitsos/publications/wang_sga2010.pdf

H. Wang, X. Chai, Y. Zhou, and X. Chen, Fast sign language recognition benefited from low rank approximation, Automatic Face and Gesture Recognition, 2015.

J. Wang, Z. Liu, Y. Wu, and J. Yuan, Learning Actionlet Ensemble for 3D Human Action Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.5, pp.914-927, 2014.
DOI : 10.1109/TPAMI.2013.198

R. Y. Wang and J. Popovi´cpopovi´c, Real-time hand-tracking with a color glove, ACM Transactions on Graphics, vol.28638, issue.3, pp.1-63, 2009.
DOI : 10.1145/1576246.1531369

Y. Wang, D. Tran, Z. Liao, and D. Forsyth, Discriminative Hierarchical Part-Based Models for Human Parsing and Action Recognition, Journal of Machine Learning Research, vol.6, issue.10, pp.13-3075, 2012.
DOI : 10.1109/CVPR.2010.5540235

Z. Wang, L. Wang, W. Du, and Q. Yu, Action spotting system using Fisher vector, CVPR ChaLearn Looking at People Workshop 2015, 2015.

A. Wexelblat, An approach to natural gesture in virtual environments, ACM Transactions on Computer-Human Interaction, vol.2, issue.3, pp.179-200, 1995.
DOI : 10.1145/210079.210080

URL : http://www.techfak.uni-bielefeld.de/techfak/ags/wbski/lehre/digiSA/MMK-Seminar/wexelblat.pdf

M. Wilhelm, A generic context aware gesture recognition framework for smart environments. Per- Com Workshops
DOI : 10.1109/percomw.2012.6197561

A. D. Wilson and A. F. Bobick, Parametric hidden Markov models for gesture recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.9, 1999.
DOI : 10.1109/34.790429

URL : http://www.research.microsoft.com/~awilson/papers/pami99.pdf

J. Wu and J. Cheng, Bayesian Co-Boosting for Multi-modal Gesture Recognition, Journal of Machine Learning Research, vol.12, issue.9, p.2014
DOI : 10.1007/BF02943243

Y. Wu and T. S. Huang, View-independent recognition of hand postures, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.88-94, 2000.

Y. Xiao, Z. Zhang, A. Beck, J. Yuan, and D. Thalmann, Human???Robot Interaction by Understanding Upper Body Gestures, Presence: Teleoperators and Virtual Environments, vol.7, issue.1, pp.133-154, 2014.
DOI : 10.1109/TMECH.2011.2181977

H. D. Yang, S. Sclaroff, and S. W. Lee, Sign Language Spotting with a Threshold Model Based on Conditional Random Fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.7, pp.311264-1277, 2009.
DOI : 10.1109/TPAMI.2008.172

URL : http://cavr.korea.ac.kr/publication/journal/08_06.pdf

M. H. Yang, N. Ahuja, and M. Tabb, Extraction of 2D motion trajectories and its application to hand gesture recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, issue.8, pp.241061-1074, 2002.

W. Yang, Y. Wang, and G. Mori, Recognizing human actions from still images with latent poses, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2030-2037, 2010.
DOI : 10.1109/CVPR.2010.5539879

URL : http://www.cs.sfu.ca/%7Emori/research/papers/yang_cvpr10.pdf

X. Yang and Y. Tian, Super Normal Vector for Activity Recognition Using Depth Sequences, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014.
DOI : 10.1109/CVPR.2014.108

URL : http://yangxd.org/publications/papers/SNV.pdf

X. Yang and Y. Tian, Action Recognition Using Super Sparse Coding Vector with Spatio-temporal Awareness, 2014.
DOI : 10.1007/978-3-319-10605-2_47

URL : http://yangxd.org/publications/papers/SSCV.pdf

G. Yao, H. Yao, X. Liu, and F. Jiang, Real time large vocabulary continuous sign language recognition based on OP/Viterbi algorithm, International Conference on Pattern Recognition, pp.312-315, 2006.

G. Yu, Z. Liu, and J. Yuan, Discriminative Orderlet Mining for Real-Time Recognition of Human-Object Interaction, ACCV, 2014.
DOI : 10.1007/978-3-319-16814-2_4

J. Yuan, Z. Liu, and Y. Wu, Discriminative Video Pattern Search for Efficient Action Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.9, pp.1728-1743, 2011.
DOI : 10.1109/TPAMI.2011.38

Z. Zafrulla, H. Brashear, T. Starner, H. Hamilton, and P. Presti, American sign language recognition with the kinect, Proceedings of the 13th international conference on multimodal interfaces, ICMI '11, pp.279-286, 2011.
DOI : 10.1145/2070481.2070532

M. Zanfir, M. Leordeanu, and C. Sminchisescu, The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection, 2013 IEEE International Conference on Computer Vision, 2013.
DOI : 10.1109/ICCV.2013.342

J. Zieren and K. Kraiss, Robust Person-Independent Visual Sign Language Recognition, Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), pp.520-528, 2005.
DOI : 10.1007/11492429_63